Lead Engineer, Pricing & Decision Systems
One Park Financial11 days ago
Miami, FL, USAStaff+
Responsibilities
- Own the Python-based pricing and decision engine, including its AWS deployment, APIs, scoring models, offer rules, data storage, audit records, and monitoring.
- Implement and integrate scoring models and maintain pricing terms, rates, fees, offer sizing, and business logic.
- Lead and mentor engineers, set architecture and coding standards, review pricing-related changes, and direct team work.
- Build reconciliation, data-quality, and QA checks for DynamoDB, S3, reference files, experiments, and pricing decisions.
- Design, run, and analyze A/B tests for pricing strategies, including eligibility, assignment, balancing, and experiment-data integrity.
- Own integrations with the sales platform, CRM, external credit and bank-data providers, and related data flows.
- Partner across Product, DevOps, Data Engineering, Data Science, and QA on roadmaps, deployments, incidents, model integration, and test coverage.
- Expand the analytics platform with internal applications, data products, model integrations, data plumbing, and engineering standards.
- Use modern AI and LLM tooling for prototyping, documentation, testing, and development.
Requirements
- At least 5 years of professional Python development building and maintaining production applications and services.
- Experience leading or mentoring engineers, setting standards, reviewing code, and directing a small team’s work.
- Experience building and maintaining REST APIs using FastAPI, Flask, or similar technologies.
- Hands-on production AWS experience, particularly with ECS/Fargate, DynamoDB, S3, Lambda, SQS, Secrets Manager, and CloudWatch.
- Experience designing DynamoDB access patterns, handling schema and type changes, and managing versioned S3 data such as Parquet and partitioned datasets.
- Strong SQL skills and comfort with relational and NoSQL data, CSV files, and Parquet files.
- Experience with business-logic-heavy systems where correctness and accurate implementation of rules are critical.
- Familiarity with data modeling and validation frameworks such as Pydantic and with reconciliation and QA checks.
- Hands-on experience integrating machine-learning or analytical model outputs into production, including feature engineering and scoring logic.
- Experience designing or supporting A/B tests and experimentation, including stratification and clean experiment data.
- Strong communication, cross-team collaboration, self-direction, and end-to-end system ownership.
- Comfort using modern AI and LLM tools to improve work efficiency.
- Preferred experience includes financial services, lending, pricing systems, CRM or platform APIs, Docker, dbt, Airflow, Next.js, TypeScript, RAG, LangChain, LangGraph, Agents SDK, MLflow, SageMaker, model monitoring, and retraining pipelines.
Benefits
- Local and national health insurance, dental and vision insurance, and Group Medical Bridge.
- 401(k) with company match.
- Company-covered ID protection and life insurance.
- Generous paid time off and holidays.
- Full-time, on-site role in Miami, United States.
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